Triple
T23674390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King’s Gallantry Medal |
E584826
|
entity |
| Predicate | hasRibbonType |
P30718
|
FINISHED |
| Object | distinctive gallantry ribbon |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: distinctive gallantry ribbon | Statement: [King’s Gallantry Medal, hasRibbonType, distinctive gallantry ribbon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRibbonType Context triple: [King’s Gallantry Medal, hasRibbonType, distinctive gallantry ribbon]
-
A.
ribbonType
chosen
Indicates the specific kind or category of ribbon associated with an entity.
-
B.
orderRibbonColor
Indicates the color assigned to the ribbon associated with a particular order.
-
C.
indicatesOnRibbon
Indicates that one entity is displayed or marked on a ribbon associated with another entity.
-
D.
ribbonHasStripe
Indicates that a ribbon features one or more stripes as part of its pattern or design.
-
E.
hasMottoRibbon
Indicates that an entity features or is associated with a ribbon element specifically used to display a motto.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e24901f7c08190909fd727632e823d |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b4f1dee08190bfe78564c65f01ad |
completed | April 29, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f118dd13008190a8799b4e9cadbd79 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:51 p.m.